Understanding Stateful LSTM Recurrent Neural Networks in Python with Keras

Last Updated on August 27, 2020 A powerful and popular recurrent neural network is the long short-term model network or LSTM. It is widely used because the architecture overcomes the vanishing and exposing gradient problem that plagues all recurrent neural networks, allowing very large and very deep networks to be created. Like other recurrent neural networks, LSTM networks maintain state, and the specifics of how this is implemented in Keras framework can be confusing. In this post you will discover […]

September 29, 2020 Machine Learning

How To Compare the Performance of Machine Learning Algorithms in Weka

Last Updated on December 11, 2019 What algorithm should you use for a given machine learning problem? This is the challenge of applied machine learning. There is no quick answer to this question, but there is a reliable process that you can use. In this post you will discover how to find good and even best machine learning algorithms for a data set by directly comparing them in Weka. After reading this post you will know: The process for discovering […]

September 29, 2020 Machine Learning

How to Tune Machine Learning Algorithms in Weka

Last Updated on December 11, 2019 You can get the most from a machine learning algorithm by tuning its parameters, called hyperparameters. In this post you will discover how to tune machine learning algorithms with controlled experiments in Weka. After reading this post you will know: The importance of improving the performance of machine learning models by algorithm tuning. How to design a controlled experiment to tune the hyperparameters of a machine learning algorithm. How to interpret the results from […]

September 29, 2020 Machine Learning

Data Leakage in Machine Learning

Last Updated on August 15, 2020 Data leakage is a big problem in machine learning when developing predictive models. Data leakage is when information from outside the training dataset is used to create the model. In this post you will discover the problem of data leakage in predictive modeling. After reading this post you will know: What is data leakage is in predictive modeling. Signs of data leakage and why it is a problem. Tips and tricks that you can […]

September 29, 2020 Machine Learning

How to Save Your Machine Learning Model and Make Predictions in Weka

Last Updated on December 11, 2019 After you have found a well performing machine learning model and tuned it, you must finalize your model so that you can make predictions on new data. In this post you will discover how to finalize your machine learning model, save it to file and load it later in order to make predictions on new data. After reading this post you will know: How to train a final version of your machine learning model […]

September 29, 2020 Machine Learning

Text Generation With LSTM Recurrent Neural Networks in Python with Keras

Last Updated on September 3, 2020 Recurrent neural networks can also be used as generative models. This means that in addition to being used for predictive models (making predictions) they can learn the sequences of a problem and then generate entirely new plausible sequences for the problem domain. Generative models like this are useful not only to study how well a model has learned a problem, but to learn more about the problem domain itself. In this post you will […]

September 29, 2020 Machine Learning

How To Work Through a Multi-Class Classification Project in Weka

Last Updated on August 22, 2019 The Weka machine learning workbench is so easy to use that working through a machine learning project can be a lot of fun. In this post you will complete your first machine learning project using Weka, end-to-end. This gentle introduction to working through a project will tie together the key steps you need to complete when working through machine learning project in Weka. After completing this project, you will know: How to analyze a […]

September 29, 2020 Machine Learning

How To Work Through a Binary Classification Project in Weka Step-By-Step

Last Updated on December 11, 2019 The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a binary classification problem in Weka, end-to-end. After reading this post you will know: How to load a dataset and analyze the loaded data. How to create multiple different transformed views of the data and evaluate a suite of algorithms on each. How to finalize and present the […]

September 29, 2020 Machine Learning

How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras

Last Updated on August 27, 2020 Hyperparameter optimization is a big part of deep learning. The reason is that neural networks are notoriously difficult to configure and there are a lot of parameters that need to be set. On top of that, individual models can be very slow to train. In this post you will discover how you can use the grid search capability from the scikit-learn python machine learning library to tune the hyperparameters of Keras deep learning models. After […]

September 29, 2020 Machine Learning

How to Work Through a Regression Machine Learning Project in Weka

Last Updated on August 22, 2019 The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a regression problem in Weka, end-to-end. After reading this post you will know: How to load and analyze a regression dataset in Weka. How to create multiple different transformed views of the data and evaluate a suite of algorithms on each. How to finalize and present the results […]

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